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Criterion
Paper illustration of a branching tree with an outcome at its root, customer opportunities, solution options and small experiment cards.
Product Discovery
Opportunity Solution Tree
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Purposedifferent
When discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure.When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
MediumHighMediumLow
Timedifferent
1-2 h Setup, laufend1-4 Wochen1-5 Tage1-5 Tage
Participantsdifferent
2-61-6NutzertrafficNutzertraffic
Formatdifferent
Workshop + asyncAsyncAsyncAsync
Outputdifferent
Opportunity Solution Tree, Experiment Backlog, Learning LogExperiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning DecisionInterest Metrics, Conversion Signal, Learning Note
Tags1 shared
DiscoveryOutcomesExperimentsOpportunity
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
ValidationExperimentsDemandGrowth
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